Machine learning & Artificial Intelligence in Audio

Mission Statement

The Technical Committee on Machine Learning and Artificial Intelligence (TC-MLAI) promotes the application of ML and AI in audio, addressing technical innovation, engineering and creative practices, data and licensing, and social, cultural, legal, and ethical considerations. The committee fosters knowledge exchange through workshops, symposia, tutorials, and technical documents.  The TC-MLAI acts as a point of contact and a bridge to other AES technical committees,  the AES community at large, and other organizations involved in ML and AI for audio.

Areas of Concentration

• AI in audio education
• Artificial intelligence and creativity
• Aspects of evaluation, both objective and perceptual
• Best practices for data and metadata handling, e.g. data collection, labeling, and storage
• Best practices for workflows, e.g. when updating, deploying and assuring quality of trained models
• Documentation of ML and AI evolution and history of ML
• Ethical and social considerations of AI applications
• Explaining and understanding decisions of data driven systems
• Licensing issues for data, pretrained models, and software implementations (external libraries)
• Machine Learning and Artificial Intelligence Algorithms
• Security and robustness